Previous approaches to automatically deblurring digital photographs have involved so called “blind” and “non blind” image deblurring.
Non blind image deblurring reconstructs a sharp image from a blurred image, given an already available blur kernel estimate. In contrast, blind image deblurring attempts to simultaneously reconstruct both a blur kernel and a sharp image.
There is an ongoing desire to improve the accuracy of image deblurring systems. Previous approaches to automatically deblurring digital photographs often introduce artifacts. For example, ringing artifacts are introduced where intensity values are inappropriately altered so that ripple-like or ghost-like effects appear around objects depicted in the image. Another problem is that smooth areas are often reconstructed at the expense of fine detail.
Existing image deblurring systems are typically not operable on devices with limited memory and processing capacity such as smart phones and embedded devices. Also, existing image deblurring systems may be slow and/or difficult to use by end users who are not familiar with image deblurring processes.
The embodiments described below are not limited to implementations which solve any or all of the disadvantages of known image deblurring systems.